In many video processing applications, in which moving objects may be displayed in a sequence of image frames, it may be useful to have knowledge of the motion which occurs from frame to frame. Examples of such applications include, frame rate conversion, deinterlacing, noise reduction, and cross-chroma reduction. In a typical method for frame rate conversion, for example one that enables doubling of the frame rate of a video sequence, each image frame may be repeated twice. By instead taking this motion information into account, one can perform adaptive processing that adapts to and compensates for the motion in the scene.
There have been many methods proposed for modeling the motion in a scene. One such method is a translational block-based model. In this model, the original frame is broken into small blocks, and the motion between frames is modeled in terms of translational shifts of these blocks. Each block is assigned a two-dimensional (horizontal/vertical) motion vector (MV) that describes the translational shift assigned to each block.
Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of skill in the art, through comparison of such systems with some aspects of the present invention as set forth in the remainder of the present application with reference to the drawings.